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Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma

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Advancing care for acute gastrointestinal bleeding using artificial intelligence.

Dennis L Shung¹

¹Yale School of Medicine, New Haven, Connecticut, USA.

Journal of Gastroenterology and Hepatology

|February 24, 2021

Summary

Machine learning (ML) enhances gastrointestinal bleeding care by improving risk assessment and decision-making. ML algorithms can identify patients, predict bleeding risk, and guide treatment, optimizing patient management.

Failed At:

2026-06-19T13:38:54.957497+00:00

Keywords:

artificial intelligence gastrointestinal hemorrhage machine learning natural language processing risk assessment

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